# interventionTable: Calculate interventional distributions. In rje: Miscellaneous Useful Functions for Statistics

 interventionMatrix R Documentation

## Calculate interventional distributions.

### Description

Calculate interventional distributions from a probability table or matrix of multivariate probability distributions.

### Usage

```interventionMatrix(x, variables, condition, dim = NULL, incols = FALSE)

interventionTable(x, variables, condition)
```

### Arguments

 `x` An array of probabilities. `variables` The margin for the intervention. `condition` The dimensions to be conditioned upon. `dim` Integer vector containing dimensions of variables. Assumed all binary if not specified. `incols` Logical specifying whether not the distributions are stored as the columns in the matrix; assumed to be rows by default.

### Details

This just divides the joint distribution p(x) by p(v | c), where v is `variables` and c is `condition`.

Under certain causal assumptions this is the interventional distribution p(x \,|\, do(v)) (i.e. if the direct causes of v are precisely c.)

`intervention.table()` is identical to `interventionTable()`.

### Value

A numerical array of the same dimension as x.

### Functions

• `interventionMatrix`: Interventions in matrix of distributions

Robin Evans

### References

Pearl, J., Causality, 2nd Edition. Cambridge University Press, 2009.

`conditionTable`, `marginTable`

### Examples

```
set.seed(413)
# matrix of distributions
p = rdirichlet(10, rep(1,16))
interventionMatrix(p, 3, 2)

# take one in an array
ap = array(p[1,], rep(2,4))
interventionTable(ap, 3, 2)

```

rje documentation built on Nov. 12, 2022, 9:06 a.m.